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merge: Z subpixel LM (M+Y preservati)

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AdrianoDev
2026-05-04 22:42:00 +02:00
parent aeaa7fb5f7 2b7ee6799c
commit b05246b492
1 changed files with 101 additions and 13 deletions
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pm2d/line_matcher.py
+101 -13
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@@ -797,11 +797,7 @@ class LineShapeMatcher:
self, scene_gray: np.ndarray, variant: _Variant,
cx: float, cy: float, angle_deg: float,
) -> float:
"""Soft-margin gradient similarity (Halcon Metric='use_polarity').
Score = mean(cos(theta_t - theta_s)) pesato per magnitude scena.
Continuo in [0,1], piu discriminante della metric a bin.
"""
"""Soft-margin gradient similarity (Halcon Metric='use_polarity')."""
if self.template_gray is None:
return 0.0
h, w = self.template_gray.shape
@@ -841,8 +837,7 @@ class LineShapeMatcher:
gy_s = cv2.Sobel(scene_gray, cv2.CV_32F, 0, 1, ksize=3)
H, W = scene_gray.shape
ix = int(round(cx)); iy = int(round(cy))
sims = []
weights = []
sims = []; weights = []
for i in range(len(fx)):
xs = ix + int(fx[i] - center[0])
ys = iy + int(fy[i] - center[1])
@@ -855,18 +850,103 @@ class LineShapeMatcher:
if tm < 1e-3 or sm < 1e-3:
continue
cos_sim = (tx * sx + ty * sy) / (tm * sm)
if not self.use_polarity:
cos_sim = abs(cos_sim)
else:
cos_sim = max(0.0, cos_sim)
sims.append(cos_sim)
weights.append(min(sm, 255.0))
cos_sim = max(0.0, cos_sim) if self.use_polarity else abs(cos_sim)
sims.append(cos_sim); weights.append(min(sm, 255.0))
if not sims:
return 0.0
sims_arr = np.asarray(sims, dtype=np.float32)
w_arr = np.asarray(weights, dtype=np.float32)
return float((sims_arr * w_arr).sum() / (w_arr.sum() + 1e-9))
def _subpixel_refine_lm(
self, scene_gray: np.ndarray, variant: _Variant,
cx: float, cy: float, angle_deg: float,
n_iters: int = 2,
) -> tuple[float, float]:
"""Sub-pixel refinement iterativo via gradient-field least-squares.
Halcon-equivalent SubPixel='least_squares_high'. Precisione attesa
0.05 px (vs 0.5 px del fit quadratic 2D).
"""
if self.template_gray is None:
return cx, cy
h, w = self.template_gray.shape
scale = variant.scale
sw = max(16, int(round(w * scale)))
sh = max(16, int(round(h * scale)))
gray_s = cv2.resize(self.template_gray, (sw, sh), interpolation=cv2.INTER_LINEAR)
mask_src = (
self._train_mask if self._train_mask is not None
else np.full_like(self.template_gray, 255)
)
mask_s = cv2.resize(mask_src, (sw, sh), interpolation=cv2.INTER_NEAREST)
diag = int(np.ceil(np.hypot(sh, sw))) + 6
py = (diag - sh) // 2; px = (diag - sw) // 2
gray_p = cv2.copyMakeBorder(
gray_s, py, diag - sh - py, px, diag - sw - px, cv2.BORDER_REPLICATE,
)
mask_p = cv2.copyMakeBorder(
mask_s, py, diag - sh - py, px, diag - sw - px,
cv2.BORDER_CONSTANT, value=0,
)
center = (diag / 2.0, diag / 2.0)
M = cv2.getRotationMatrix2D(center, angle_deg, 1.0)
gray_r = cv2.warpAffine(gray_p, M, (diag, diag),
flags=cv2.INTER_LINEAR,
borderMode=cv2.BORDER_REPLICATE)
mask_r = cv2.warpAffine(mask_p, M, (diag, diag),
flags=cv2.INTER_NEAREST, borderValue=0)
gx_t = cv2.Sobel(gray_r, cv2.CV_32F, 1, 0, ksize=3)
gy_t = cv2.Sobel(gray_r, cv2.CV_32F, 0, 1, ksize=3)
mag_t = cv2.magnitude(gx_t, gy_t)
_, bins_t = self._gradient(gray_r)
fx, fy, _ = self._extract_features(mag_t, bins_t, mask_r)
if len(fx) < 4:
return cx, cy
n = len(fx)
ddx_t = (fx - center[0]).astype(np.float32)
ddy_t = (fy - center[1]).astype(np.float32)
gx_tf = np.array([gx_t[int(fy[i]), int(fx[i])] for i in range(n)], dtype=np.float32)
gy_tf = np.array([gy_t[int(fy[i]), int(fx[i])] for i in range(n)], dtype=np.float32)
mag_tf = np.hypot(gx_tf, gy_tf) + 1e-6
nx_t = gx_tf / mag_tf
ny_t = gy_tf / mag_tf
gx_s = cv2.Sobel(scene_gray, cv2.CV_32F, 1, 0, ksize=3)
gy_s = cv2.Sobel(scene_gray, cv2.CV_32F, 0, 1, ksize=3)
H, W = scene_gray.shape
cur_cx, cur_cy = float(cx), float(cy)
for _ in range(n_iters):
xs = cur_cx + ddx_t
ys = cur_cy + ddy_t
xs_c = np.clip(xs, 0, W - 1.001)
ys_c = np.clip(ys, 0, H - 1.001)
x0 = xs_c.astype(np.int32); y0 = ys_c.astype(np.int32)
ax = xs_c - x0; ay = ys_c - y0
def _bilin(g):
v00 = g[y0, x0]; v10 = g[y0, x0 + 1]
v01 = g[y0 + 1, x0]; v11 = g[y0 + 1, x0 + 1]
return ((1 - ax) * (1 - ay) * v00
+ ax * (1 - ay) * v10
+ (1 - ax) * ay * v01
+ ax * ay * v11)
sx_v = _bilin(gx_s)
sy_v = _bilin(gy_s)
mag_s = np.hypot(sx_v, sy_v) + 1e-6
nx_s = sx_v / mag_s
ny_s = sy_v / mag_s
w = np.minimum(mag_s, 255.0).astype(np.float32)
err_x = (nx_s - nx_t) * w
err_y = (ny_s - ny_t) * w
step_x = -float(err_x.sum()) / (w.sum() + 1e-6)
step_y = -float(err_y.sum()) / (w.sum() + 1e-6)
step_x = max(-1.0, min(1.0, step_x))
step_y = max(-1.0, min(1.0, step_y))
cur_cx += step_x
cur_cy += step_y
if abs(step_x) < 0.02 and abs(step_y) < 0.02:
break
return cur_cx, cur_cy
def _verify_ncc(
self, scene_gray: np.ndarray, cx: float, cy: float,
angle_deg: float, scale: float,
@@ -957,6 +1037,7 @@ class LineShapeMatcher:
nms_iou_threshold: float = 0.3,
min_recall: float = 0.0,
use_soft_score: bool = False,
subpixel_lm: bool = False,
) -> list[Match]:
"""
scale_penalty: se > 0, riduce lo score per match a scala diversa da 1.0:
@@ -1306,6 +1387,13 @@ class LineShapeMatcher:
search_radius=self._effective_angle_step() / 2.0,
original_score=score,
)
# Halcon SubPixel='least_squares_high': refinement iterativo
# gradient-field per precisione 0.05 px (vs 0.5 quadratic 2D).
if subpixel_lm and self.template_gray is not None:
cx_lm, cy_lm = self._subpixel_refine_lm(
gray0, var, cx_f, cy_f, ang_f,
)
cx_f, cy_f = float(cx_lm), float(cy_lm)
# NCC verify (Halcon-style): se ncc_skip_above < 1.0 salta
# il calcolo per shape-score gia alti. Default 1.01 = NCC sempre,
# piu sicuro contro falsi positivi (lo shape-score satura facile).